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Constant-Time Arithmetic for Safer Cryptography

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Constant-Time Arithmetic for Safer Cryptography Constant-Time Arithmetic for Safer Cryptography Lúcás Críostóir Meier1, Simone Colombo1, Marin Thiercelin2, and Bryan Ford1 1DEDIS, EPFL, Switzerland {lucascriostoir.meier, simone.colombo, bryan.ford}@epfl.ch 2ProtonMail, Switzerland [email protected] Abstract The humble integers, Z, are the backbone of many cryptosystems. When bridging the gap from theoretical systems to real-world implementations, programmers often look towards general purpose libraries to implement the arbitrary-precision arithmetic required. Alas, these libraries are often conceived without cryptography in mind, leaving applications potentially vulnerable to timing attacks. To address this, we present saferith, a library providing safer arbitrary-precision arithmetic for cryptography, through constant-time operations. The main challenge was in designing an API to provide this functionality alongside these stronger constant-time guarantees. We benchmarked the performance of our library against Go’s big.Int library, and found an acceptable slowdown of only 2.56× for modular exponentiation, the most expensive operation. Our library was also used to implement a variety cryptosystems and applications, in collaboration with industrial partners ProtonMail and Taurus. Porting implementations to use our library is relatively easy: it took the first author under 8 hours to port Go’s implementation of P-384. 1 Introduction At CRYPTO ’96, Kocher [Koc96] warned the cryptographic community about the risks of timing attacks against public-key cryptosystems. Twenty-five years later, cryptographic implementa- tions are ubiquitous; the risks of these attacks as well. Timing attacks enable an adversary to extract secrets, such as private keys or plaintexts, from a system, by measuring the time it takes to perform sensitive operations, such as decryption. These attacks often arise from the increasingly complex micro-architecture used to implement operations in hardware [GYCH18]. They can even be carried out over a network [BB05, BT11], and have lead to concrete attacks against AES [Ber05, OST06], RSA [AKS06, AKS07, YGH17, CAPGATB19], and Diffie-Hellman ¸ key exchange [MBA 19]. To avoid these attacks, it is possible to write constant-time programs, in which operations only vary in time based on public values. This involves various techniques [Aum20], such as replacing branches with bitwise operations, avoiding array accesses with secret indices, or making sure that loops have a fixed number of iterations. Constant-time operations are easier to implement with values that have a fixed size. This is the case for many modern cryptosystems, which often use finite fields with fixed parameters. In this case, each set of parameters can have an optimized—and constant-time—implementation. 1 Unfortunately, some cryptosystems, like RSA [RSA78], or Paillier [Pai99], do not have fixed pa- rameters. Instead, these parameters are part of the public key. In this case, arbitrary-precision arithmetic is necessary, which requires more care to design a constant-time implementation. While most programming languages have popular libraries providing arbitrary-precision arith- metic, they are, alas, not designed with cryptography in mind, leaving them vulnerable to timing attacks. Go [Aut], in particular, suffers from these issues. Go provides the big.Int type for working with arbitrary-precision signed integers. Although the authors provide no guarantees of constant- time operations, big.Int gets used for cryptography, even inside of Go’s standard library. This is especially concerning, as an increasing amount of cryptographic software is written in Go. To provide arbitrary-precision arithmetic with the constant-time properties needed for cryptog- raphy, we created the saferith library [Mei21], implemented in Go. The main challenge of our work was in designing an API providing all the functionality needed from big.Int, as well as the additional constant-time guarantees needed for cryptography. This involved synthesizing the variety of timing-attacks into a succinct threat model, as well as determining how to safely manipulate arbitrary-precision integers, even though operations vary in execution time based on the size of numbers. The crux of our solution is to pad numbers to different public sizes. While operations may leak this public size, the underlying value is kept hidden. To evaluate our library, we created a couple of experiments to compare the constant-time execu- tion of our library with the variable-time execution of big.Int. We also ran micro-benchmarks showing that these extra guarantees come only at a performance cost of 2.56× for exponentiation, the most expensive arithmetic operation. To test the practicality of our library, we modified Go’s implementations of RSA and NIST’s P-384 curve [CMRR19] to use saferith. We also worked with industrial partners to port their applications to use our library. ProtonMail ported their implementation of the Secure Remote Password (SRP) protocol [Wu97] away from big.Int. With Taurus, we integrated our library ¸ into their implementation [HMA21] of the CGG+ Threshold ECDSA protocol [CGG 20]. This state-of-the-art protocol is used by Fireblocks, among others, to secure their implementation of cryptocurrency wallets1. In summary, our contributions are: • A succinct threat-model for timing-attacks against arbitrary-precision arithmetic libraries. • A language-agnostic API for constant-time execution of arbitrary-precision arithmetic operations. • An efficient Go library providing constant-time arbitrary-precision arithmetic. • An evaluation of the library using micro-benchmarks and implementations of real-world protocols with industrial partners. 2 Background In this section, we review timing side-channel attacks. We focus in particular on attacks targeting arbitrary-precision arithmetic libraries and the Go’s standard cryptography library. 1https://apnews.com/press-release/pr-newswire/26aab91e254bc254d331ceafc20b9859 2 2.1 Timing Side-Channels A timing side-channel [Koc96, KSWH98] arises when an implementation of some algorithm leaks information about the values it processes through observable timing patterns. When a program performs more operations based on the value of its inputs, it inevitably leaks information about those inputs: their values can be inferred by observing how many operations were performed. Additionally, programs performing a fixed number of operations may have timing leaks because of how the underlying hardware implements these operations. These micro-architectural attacks are covered in more detail in our threat model (Section 3.1), as well as in the survey by Ge et al. [GYCH18]. 2.2 Arbitrary-Precision Arithmetic in Practice Many programming languages have a general-purpose type for arbitrary-precision arithmetic in their standard library, or a prominent one in their ecosystem. For example, Python, Haskell, and Go all have arbitrary-precision arithmetic types in their standard libraries, while Rust has the num-bigint library, and C has GMP. These types provide no guarantees around constant-time operations. Yet, for lack of better alternatives, they do get used for cryptography. From this perspective, these types suffer from two major issues. The first issue is that algorithms branch or access memory based on input values. For example, exponentiation may branch on the bits of the exponent. Not using constant-time implemen- tations of these algorithms is understandable: these libraries are not intended to be used in cryptography. The second, more fundamental, issue is that these libraries store numbers with- out any zero padding. Numbers are represented as a sequence of register sized limbs, analogous to bit sized digits. Numbers are stored normalized, with leading zero limbs removed. Even if an operation produces an output of a given length, the result is truncated based on its value. Because operations inevitably vary in time based on the number of limbs a value is stored with, removing this padding can make certain values produce considerably different timing patterns. While timing vulnerabilities like these are concerning in theory, they may not always lead to practical attacks. Certain operations are particularly vulnerable, such as exponentiation. A recent paper by De Feo et al. [FPS21] analyzed, among other things, Go’s implementation of DSA with its own big.Int type, and found that it was practically exploitable. The problem was that big.Int’s exponentiation method uses direct table lookups, making it vulnerable to a cache-based timing attack. More subtle vulnerabilities can come from the pervasive padding issues mentioned above: the OpenSSL library was affected by a similar issue for over 20 years, as recently exposed by Merget ¸ et al. [MBA 19]. 2.3 Go: A Case Study We have chosen Go [Aut] as a poignant example of how vulnerable arbitrary-precision arithmetic libraries see widespread usage. Go provides a type for arbitrary-precision arithmetic in its standard library: big.Int. Despite suffering from the many shortcomings highlighted above, it is widely used in cryptography, including inside of Go’s own standard cryptography package: go/crypto. Inside this package, there are three cryptographic schemes which make use of big.Int. 3 In DSA, big.Int is used for signing and verification. While this implementation is marked as deprecated by the Go authors, it is nonetheless imported by more than two thousand known packages. In RSA, Go embeds big.Int as part of the API for the package. Key-generation, encryption, decryption, signing,
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